A novel dopamine transporter transgenic mouse line for identification and purification of midbrain dopaminergic neurons reveals midbrain heterogeneity
Bibliographic record
Abstract
Midbrain dopaminergic (DAergic) neurons are a heterogeneous cell group, composed of functionally distinct cell populations projecting to the basal ganglia, prefrontal cortex and limbic system. Despite their functional significance, the midbrain population of DAergic neurons is sparse, constituting only 20 000-30 000 neurons in mice, and development of novel tools to identify these cells is warranted. Here, a bacterial artificial chromosome mouse line [Dat1-enhanced green fluorescent protein (eGFP)] from the Gene Expression Nervous System Atlas (GENSAT) that expresses eGFP under control of the dopamine transporter (DAT) promoter was characterized. Confocal microscopy analysis of brain sections showed strong eGFP signal reporter in midbrain regions and striatal terminals that co-localized with the DAergic markers DAT and tyrosine hydroxylase (TH). Thorough quantification of co-localization of the eGFP reporter signal with DAT and TH in the ventral midbrain showed that a vast majority of eGFP-expressing neurons are DAergic. Importantly, expression profiles also revealed DAergic heterogeneity when comparing substantia nigra and ventral tegmental area. Dat1-eGFP mice showed neither change in synaptosomal DA uptake nor altered levels of DAT and TH in both striatum and midbrain. No behavioural difference between Dat1-eGFP and wild-type was found, suggesting that the strain is not aberrant. Finally, cell populations highly enriched in DAergic neurons can be obtained from postnatal mice by fluorescence-activated cell sorting and the sorted neurons can be cultured in vitro. The current investigation demonstrates that eGFP expression in this mouse line is selective for DAergic neurons, suggesting that the Dat1-eGFP mouse strain constitutes a promising tool for delineating new aspects of DA biology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".